Deployment of threat agents poses significant threats to both human and economic health. The threat is compounded by a limited ability to detect deployment of the agents. Prior art detection strategies rely on separate instrumentation for detection and identification of the threat agent. Conventional means of detecting airborne matter include relatively non-specific optical and spectroscopic methods, including laser scattering and ultraviolet laser induced fluorescence (UV-LIF). Conventional means to identify a threat agent include wet chemical methods or spectroscopic methods. Reagent-based identification of biological threat agents includes methods such as specific antibodies, genetic markers and propagation in culture. While highly specific, these identification methods are time-consuming, labor-intensive and costly.
Spectroscopic means, for identification, provide an alternative to reagent-based identification methods and include mass spectrometry, infrared spectroscopy, Raman spectroscopy, laser induced breakdown spectroscopy (LIBS), and imaging spectrometry. Mass spectrometry is limited by sensitivity to background interference. Infrared spectroscopy exhibits low sensitivity. Raman spectroscopy is a good candidate for detection of threat agents based on its ability to provide a molecular “fingerprint” for materials with high specificity. Raman spectroscopy can be implemented in several different configurations, including normal Raman spectroscopy, UV resonance Raman spectroscopy, surface enhanced Raman spectroscopy (SERS) and non-linear Raman spectroscopy.
While normal Raman spectroscopy has demonstrated adequate sensitivity and specificity for detection of airborne matter, other forms of Raman spectroscopy suffer from inadequate sensitivity, specificity or signature robustness. LIES is also a good candidate for detection of threat agents based on its ability provide an elemental “fingerprint” for materials with high sensitivity. Prior art imaging spectroscopy is limited by the need to switch from a broadband light source, for optical imaging, to a substantially monochromatic light source for spectroscopic imaging. This results in a signification delay and inefficiency during detection during which the sample may degrade.
In order to improve the overall sensitivity and specificity of a fieldable threat detection, the invention combines two well known and proven techniques, Raman and LIBS, into a system optimized for threat detection. Both individual methods have demonstrated the ability to detect threats in point sensing, proximity sensing and standoff sensing configurations. Improved overall detection performance can be realized through appropriate chemometric spectral processing algorithms applied to the fused data of the two orthogonal techniques. By combining Raman and LIBS techniques, threat detection performance can be improved relative to the individual techniques acting alone.